Overview

Brought to you by YData

Dataset statistics

Number of variables43
Number of observations1460
Missing cells7481
Missing cells (%)11.9%
Total size in memory490.6 KiB
Average record size in memory344.1 B

Variable types

Text43

Alerts

Fence has 1179 (80.8%) missing values Missing
FireplaceQu has 690 (47.3%) missing values Missing
PoolQC has 1453 (99.5%) missing values Missing
GarageQual has 81 (5.5%) missing values Missing
BsmtFinType1 has 37 (2.5%) missing values Missing
BsmtQual has 37 (2.5%) missing values Missing
Alley has 1369 (93.8%) missing values Missing
GarageType has 81 (5.5%) missing values Missing
GarageCond has 81 (5.5%) missing values Missing
MasVnrType has 872 (59.7%) missing values Missing
BsmtCond has 37 (2.5%) missing values Missing
GarageFinish has 81 (5.5%) missing values Missing
MiscFeature has 1406 (96.3%) missing values Missing
BsmtFinType2 has 38 (2.6%) missing values Missing
BsmtExposure has 38 (2.6%) missing values Missing

Reproduction

Analysis started2025-08-10 21:59:09.010464
Analysis finished2025-08-10 21:59:09.619153
Duration0.61 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:09.713555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4380
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReg
2nd rowReg
3rd rowIR1
4th rowIR1
5th rowIR1
ValueCountFrequency (%)
reg 925
63.4%
ir1 484
33.2%
ir2 41
 
2.8%
ir3 10
 
0.7%
2025-08-11T00:59:09.915159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 1460
33.3%
e 925
21.1%
g 925
21.1%
I 535
 
12.2%
1 484
 
11.1%
2 41
 
0.9%
3 10
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4380
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
R 1460
33.3%
e 925
21.1%
g 925
21.1%
I 535
 
12.2%
1 484
 
11.1%
2 41
 
0.9%
3 10
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4380
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
R 1460
33.3%
e 925
21.1%
g 925
21.1%
I 535
 
12.2%
1 484
 
11.1%
2 41
 
0.9%
3 10
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4380
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
R 1460
33.3%
e 925
21.1%
g 925
21.1%
I 535
 
12.2%
1 484
 
11.1%
2 41
 
0.9%
3 10
 
0.2%

Street
Text

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:10.033837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters5840
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPave
2nd rowPave
3rd rowPave
4th rowPave
5th rowPave
ValueCountFrequency (%)
pave 1454
99.6%
grvl 6
 
0.4%
2025-08-11T00:59:10.255174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
v 1460
25.0%
P 1454
24.9%
a 1454
24.9%
e 1454
24.9%
G 6
 
0.1%
r 6
 
0.1%
l 6
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5840
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
v 1460
25.0%
P 1454
24.9%
a 1454
24.9%
e 1454
24.9%
G 6
 
0.1%
r 6
 
0.1%
l 6
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5840
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
v 1460
25.0%
P 1454
24.9%
a 1454
24.9%
e 1454
24.9%
G 6
 
0.1%
r 6
 
0.1%
l 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5840
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
v 1460
25.0%
P 1454
24.9%
a 1454
24.9%
e 1454
24.9%
G 6
 
0.1%
r 6
 
0.1%
l 6
 
0.1%

Fence
Text

Missing 

Distinct4
Distinct (%)1.4%
Missing1179
Missing (%)80.8%
Memory size11.5 KiB
2025-08-11T00:59:10.403870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.768683274
Min length4

Characters and Unicode

Total characters1340
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMnPrv
2nd rowGdWo
3rd rowGdPrv
4th rowMnPrv
5th rowGdPrv
ValueCountFrequency (%)
mnprv 157
55.9%
gdprv 59
 
21.0%
gdwo 54
 
19.2%
mnww 11
 
3.9%
2025-08-11T00:59:10.648953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 216
16.1%
P 216
16.1%
v 216
16.1%
M 168
12.5%
n 168
12.5%
G 113
8.4%
d 113
8.4%
W 65
 
4.9%
o 54
 
4.0%
w 11
 
0.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1340
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 216
16.1%
P 216
16.1%
v 216
16.1%
M 168
12.5%
n 168
12.5%
G 113
8.4%
d 113
8.4%
W 65
 
4.9%
o 54
 
4.0%
w 11
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1340
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 216
16.1%
P 216
16.1%
v 216
16.1%
M 168
12.5%
n 168
12.5%
G 113
8.4%
d 113
8.4%
W 65
 
4.9%
o 54
 
4.0%
w 11
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1340
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 216
16.1%
P 216
16.1%
v 216
16.1%
M 168
12.5%
n 168
12.5%
G 113
8.4%
d 113
8.4%
W 65
 
4.9%
o 54
 
4.0%
w 11
 
0.8%

FireplaceQu
Text

Missing 

Distinct5
Distinct (%)0.6%
Missing690
Missing (%)47.3%
Memory size11.5 KiB
2025-08-11T00:59:10.863537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1540
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTA
2nd rowTA
3rd rowGd
4th rowTA
5th rowGd
ValueCountFrequency (%)
gd 380
49.4%
ta 313
40.6%
fa 33
 
4.3%
ex 24
 
3.1%
po 20
 
2.6%
2025-08-11T00:59:11.106317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 380
24.7%
d 380
24.7%
T 313
20.3%
A 313
20.3%
F 33
 
2.1%
a 33
 
2.1%
E 24
 
1.6%
x 24
 
1.6%
P 20
 
1.3%
o 20
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1540
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 380
24.7%
d 380
24.7%
T 313
20.3%
A 313
20.3%
F 33
 
2.1%
a 33
 
2.1%
E 24
 
1.6%
x 24
 
1.6%
P 20
 
1.3%
o 20
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1540
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 380
24.7%
d 380
24.7%
T 313
20.3%
A 313
20.3%
F 33
 
2.1%
a 33
 
2.1%
E 24
 
1.6%
x 24
 
1.6%
P 20
 
1.3%
o 20
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1540
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 380
24.7%
d 380
24.7%
T 313
20.3%
A 313
20.3%
F 33
 
2.1%
a 33
 
2.1%
E 24
 
1.6%
x 24
 
1.6%
P 20
 
1.3%
o 20
 
1.3%
Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:11.249269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2920
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGd
2nd rowTA
3rd rowGd
4th rowGd
5th rowGd
ValueCountFrequency (%)
ta 735
50.3%
gd 586
40.1%
ex 100
 
6.8%
fa 39
 
2.7%
2025-08-11T00:59:11.512053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 735
25.2%
A 735
25.2%
G 586
20.1%
d 586
20.1%
E 100
 
3.4%
x 100
 
3.4%
F 39
 
1.3%
a 39
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 735
25.2%
A 735
25.2%
G 586
20.1%
d 586
20.1%
E 100
 
3.4%
x 100
 
3.4%
F 39
 
1.3%
a 39
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 735
25.2%
A 735
25.2%
G 586
20.1%
d 586
20.1%
E 100
 
3.4%
x 100
 
3.4%
F 39
 
1.3%
a 39
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 735
25.2%
A 735
25.2%
G 586
20.1%
d 586
20.1%
E 100
 
3.4%
x 100
 
3.4%
F 39
 
1.3%
a 39
 
1.3%
Distinct25
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:11.733669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.494520548
Min length5

Characters and Unicode

Total characters9482
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCollgCr
2nd rowVeenker
3rd rowCollgCr
4th rowCrawfor
5th rowNoRidge
ValueCountFrequency (%)
names 225
15.4%
collgcr 150
 
10.3%
oldtown 113
 
7.7%
edwards 100
 
6.8%
somerst 86
 
5.9%
gilbert 79
 
5.4%
nridght 77
 
5.3%
sawyer 74
 
5.1%
nwames 73
 
5.0%
sawyerw 59
 
4.0%
Other values (15) 424
29.0%
2025-08-11T00:59:12.101703image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 931
 
9.8%
e 905
 
9.5%
l 622
 
6.6%
d 506
 
5.3%
s 486
 
5.1%
o 483
 
5.1%
m 439
 
4.6%
N 425
 
4.5%
w 414
 
4.4%
C 407
 
4.3%
Other values (28) 3864
40.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9482
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 931
 
9.8%
e 905
 
9.5%
l 622
 
6.6%
d 506
 
5.3%
s 486
 
5.1%
o 483
 
5.1%
m 439
 
4.6%
N 425
 
4.5%
w 414
 
4.4%
C 407
 
4.3%
Other values (28) 3864
40.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9482
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 931
 
9.8%
e 905
 
9.5%
l 622
 
6.6%
d 506
 
5.3%
s 486
 
5.1%
o 483
 
5.1%
m 439
 
4.6%
N 425
 
4.5%
w 414
 
4.4%
C 407
 
4.3%
Other values (28) 3864
40.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9482
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 931
 
9.8%
e 905
 
9.5%
l 622
 
6.6%
d 506
 
5.3%
s 486
 
5.1%
o 483
 
5.1%
m 439
 
4.6%
N 425
 
4.5%
w 414
 
4.4%
C 407
 
4.3%
Other values (28) 3864
40.8%
Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:12.265430image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.157534247
Min length6

Characters and Unicode

Total characters8990
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNormal
2nd rowNormal
3rd rowNormal
4th rowAbnorml
5th rowNormal
ValueCountFrequency (%)
normal 1198
82.1%
partial 125
 
8.6%
abnorml 101
 
6.9%
family 20
 
1.4%
alloca 12
 
0.8%
adjland 4
 
0.3%
2025-08-11T00:59:12.518565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1484
16.5%
l 1468
16.3%
r 1424
15.8%
m 1319
14.7%
o 1311
14.6%
N 1198
13.3%
i 145
 
1.6%
P 125
 
1.4%
t 125
 
1.4%
A 117
 
1.3%
Other values (8) 274
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8990
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1484
16.5%
l 1468
16.3%
r 1424
15.8%
m 1319
14.7%
o 1311
14.6%
N 1198
13.3%
i 145
 
1.6%
P 125
 
1.4%
t 125
 
1.4%
A 117
 
1.3%
Other values (8) 274
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8990
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1484
16.5%
l 1468
16.3%
r 1424
15.8%
m 1319
14.7%
o 1311
14.6%
N 1198
13.3%
i 145
 
1.6%
P 125
 
1.4%
t 125
 
1.4%
A 117
 
1.3%
Other values (8) 274
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8990
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1484
16.5%
l 1468
16.3%
r 1424
15.8%
m 1319
14.7%
o 1311
14.6%
N 1198
13.3%
i 145
 
1.6%
P 125
 
1.4%
t 125
 
1.4%
A 117
 
1.3%
Other values (8) 274
 
3.0%
Distinct16
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:12.725409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.973287671
Min length5

Characters and Unicode

Total characters10181
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st rowVinylSd
2nd rowMetalSd
3rd rowVinylSd
4th rowWd Shng
5th rowVinylSd
ValueCountFrequency (%)
vinylsd 504
29.6%
wd 235
13.8%
metalsd 214
12.6%
hdboard 207
12.2%
sdng 197
 
11.6%
plywood 142
 
8.3%
cmentbd 60
 
3.5%
shng 38
 
2.2%
stucco 26
 
1.5%
brkface 25
 
1.5%
Other values (8) 54
 
3.2%
2025-08-11T00:59:13.061625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1766
17.3%
S 1017
 
10.0%
l 861
 
8.5%
n 834
 
8.2%
y 646
 
6.3%
o 523
 
5.1%
V 504
 
5.0%
i 504
 
5.0%
a 446
 
4.4%
t 316
 
3.1%
Other values (23) 2764
27.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10181
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
d 1766
17.3%
S 1017
 
10.0%
l 861
 
8.5%
n 834
 
8.2%
y 646
 
6.3%
o 523
 
5.1%
V 504
 
5.0%
i 504
 
5.0%
a 446
 
4.4%
t 316
 
3.1%
Other values (23) 2764
27.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10181
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
d 1766
17.3%
S 1017
 
10.0%
l 861
 
8.5%
n 834
 
8.2%
y 646
 
6.3%
o 523
 
5.1%
V 504
 
5.0%
i 504
 
5.0%
a 446
 
4.4%
t 316
 
3.1%
Other values (23) 2764
27.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10181
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
d 1766
17.3%
S 1017
 
10.0%
l 861
 
8.5%
n 834
 
8.2%
y 646
 
6.3%
o 523
 
5.1%
V 504
 
5.0%
i 504
 
5.0%
a 446
 
4.4%
t 316
 
3.1%
Other values (23) 2764
27.1%
Distinct5
Distinct (%)0.3%
Missing1
Missing (%)0.1%
Memory size11.5 KiB
2025-08-11T00:59:13.196202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.998629198
Min length3

Characters and Unicode

Total characters7293
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowSBrkr
2nd rowSBrkr
3rd rowSBrkr
4th rowSBrkr
5th rowSBrkr
ValueCountFrequency (%)
sbrkr 1334
91.4%
fusea 94
 
6.4%
fusef 27
 
1.9%
fusep 3
 
0.2%
mix 1
 
0.1%
2025-08-11T00:59:13.465251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 2668
36.6%
S 1334
18.3%
B 1334
18.3%
k 1334
18.3%
F 151
 
2.1%
u 124
 
1.7%
s 124
 
1.7%
e 124
 
1.7%
A 94
 
1.3%
P 3
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7293
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 2668
36.6%
S 1334
18.3%
B 1334
18.3%
k 1334
18.3%
F 151
 
2.1%
u 124
 
1.7%
s 124
 
1.7%
e 124
 
1.7%
A 94
 
1.3%
P 3
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7293
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 2668
36.6%
S 1334
18.3%
B 1334
18.3%
k 1334
18.3%
F 151
 
2.1%
u 124
 
1.7%
s 124
 
1.7%
e 124
 
1.7%
A 94
 
1.3%
P 3
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7293
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 2668
36.6%
S 1334
18.3%
B 1334
18.3%
k 1334
18.3%
F 151
 
2.1%
u 124
 
1.7%
s 124
 
1.7%
e 124
 
1.7%
A 94
 
1.3%
P 3
 
< 0.1%
Other values (3) 3
 
< 0.1%

PoolQC
Text

Missing 

Distinct3
Distinct (%)42.9%
Missing1453
Missing (%)99.5%
Memory size11.5 KiB
2025-08-11T00:59:13.589439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters14
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEx
2nd rowFa
3rd rowGd
4th rowEx
5th rowGd
ValueCountFrequency (%)
gd 3
42.9%
ex 2
28.6%
fa 2
28.6%
2025-08-11T00:59:13.824068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 3
21.4%
d 3
21.4%
E 2
14.3%
x 2
14.3%
F 2
14.3%
a 2
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 3
21.4%
d 3
21.4%
E 2
14.3%
x 2
14.3%
F 2
14.3%
a 2
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 3
21.4%
d 3
21.4%
E 2
14.3%
x 2
14.3%
F 2
14.3%
a 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 3
21.4%
d 3
21.4%
E 2
14.3%
x 2
14.3%
F 2
14.3%
a 2
14.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:13.959398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters8760
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowAllPub
2nd rowAllPub
3rd rowAllPub
4th rowAllPub
5th rowAllPub
ValueCountFrequency (%)
allpub 1459
99.9%
nosewa 1
 
0.1%
2025-08-11T00:59:14.208575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 2918
33.3%
A 1459
16.7%
P 1459
16.7%
u 1459
16.7%
b 1459
16.7%
N 1
 
< 0.1%
o 1
 
< 0.1%
S 1
 
< 0.1%
e 1
 
< 0.1%
W 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8760
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 2918
33.3%
A 1459
16.7%
P 1459
16.7%
u 1459
16.7%
b 1459
16.7%
N 1
 
< 0.1%
o 1
 
< 0.1%
S 1
 
< 0.1%
e 1
 
< 0.1%
W 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8760
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 2918
33.3%
A 1459
16.7%
P 1459
16.7%
u 1459
16.7%
b 1459
16.7%
N 1
 
< 0.1%
o 1
 
< 0.1%
S 1
 
< 0.1%
e 1
 
< 0.1%
W 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8760
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 2918
33.3%
A 1459
16.7%
P 1459
16.7%
u 1459
16.7%
b 1459
16.7%
N 1
 
< 0.1%
o 1
 
< 0.1%
S 1
 
< 0.1%
e 1
 
< 0.1%
W 1
 
< 0.1%

GarageQual
Text

Missing 

Distinct5
Distinct (%)0.4%
Missing81
Missing (%)5.5%
Memory size11.5 KiB
2025-08-11T00:59:14.297477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2758
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTA
2nd rowTA
3rd rowTA
4th rowTA
5th rowTA
ValueCountFrequency (%)
ta 1311
95.1%
fa 48
 
3.5%
gd 14
 
1.0%
ex 3
 
0.2%
po 3
 
0.2%
2025-08-11T00:59:14.502454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 1311
47.5%
A 1311
47.5%
F 48
 
1.7%
a 48
 
1.7%
G 14
 
0.5%
d 14
 
0.5%
E 3
 
0.1%
x 3
 
0.1%
P 3
 
0.1%
o 3
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2758
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 1311
47.5%
A 1311
47.5%
F 48
 
1.7%
a 48
 
1.7%
G 14
 
0.5%
d 14
 
0.5%
E 3
 
0.1%
x 3
 
0.1%
P 3
 
0.1%
o 3
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2758
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 1311
47.5%
A 1311
47.5%
F 48
 
1.7%
a 48
 
1.7%
G 14
 
0.5%
d 14
 
0.5%
E 3
 
0.1%
x 3
 
0.1%
P 3
 
0.1%
o 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2758
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 1311
47.5%
A 1311
47.5%
F 48
 
1.7%
a 48
 
1.7%
G 14
 
0.5%
d 14
 
0.5%
E 3
 
0.1%
x 3
 
0.1%
P 3
 
0.1%
o 3
 
0.1%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:14.598392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2920
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowTA
2nd rowTA
3rd rowTA
4th rowTA
5th rowTA
ValueCountFrequency (%)
ta 1282
87.8%
gd 146
 
10.0%
fa 28
 
1.9%
ex 3
 
0.2%
po 1
 
0.1%
2025-08-11T00:59:14.812307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 1282
43.9%
A 1282
43.9%
G 146
 
5.0%
d 146
 
5.0%
F 28
 
1.0%
a 28
 
1.0%
E 3
 
0.1%
x 3
 
0.1%
P 1
 
< 0.1%
o 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 1282
43.9%
A 1282
43.9%
G 146
 
5.0%
d 146
 
5.0%
F 28
 
1.0%
a 28
 
1.0%
E 3
 
0.1%
x 3
 
0.1%
P 1
 
< 0.1%
o 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 1282
43.9%
A 1282
43.9%
G 146
 
5.0%
d 146
 
5.0%
F 28
 
1.0%
a 28
 
1.0%
E 3
 
0.1%
x 3
 
0.1%
P 1
 
< 0.1%
o 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 1282
43.9%
A 1282
43.9%
G 146
 
5.0%
d 146
 
5.0%
F 28
 
1.0%
a 28
 
1.0%
E 3
 
0.1%
x 3
 
0.1%
P 1
 
< 0.1%
o 1
 
< 0.1%
Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:14.942944image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.006849315
Min length4

Characters and Unicode

Total characters5850
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st rowNorm
2nd rowNorm
3rd rowNorm
4th rowNorm
5th rowNorm
ValueCountFrequency (%)
norm 1445
99.0%
feedr 6
 
0.4%
artery 2
 
0.1%
rrnn 2
 
0.1%
posn 2
 
0.1%
posa 1
 
0.1%
rran 1
 
0.1%
rrae 1
 
0.1%
2025-08-11T00:59:15.222198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 1455
24.9%
N 1449
24.8%
o 1448
24.8%
m 1445
24.7%
e 15
 
0.3%
R 8
 
0.1%
F 6
 
0.1%
d 6
 
0.1%
A 5
 
0.1%
n 3
 
0.1%
Other values (4) 10
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5850
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 1455
24.9%
N 1449
24.8%
o 1448
24.8%
m 1445
24.7%
e 15
 
0.3%
R 8
 
0.1%
F 6
 
0.1%
d 6
 
0.1%
A 5
 
0.1%
n 3
 
0.1%
Other values (4) 10
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5850
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 1455
24.9%
N 1449
24.8%
o 1448
24.8%
m 1445
24.7%
e 15
 
0.3%
R 8
 
0.1%
F 6
 
0.1%
d 6
 
0.1%
A 5
 
0.1%
n 3
 
0.1%
Other values (4) 10
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5850
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 1455
24.9%
N 1449
24.8%
o 1448
24.8%
m 1445
24.7%
e 15
 
0.3%
R 8
 
0.1%
F 6
 
0.1%
d 6
 
0.1%
A 5
 
0.1%
n 3
 
0.1%
Other values (4) 10
 
0.2%
Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:15.312454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4380
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLvl
2nd rowLvl
3rd rowLvl
4th rowLvl
5th rowLvl
ValueCountFrequency (%)
lvl 1311
89.8%
bnk 63
 
4.3%
hls 50
 
3.4%
low 36
 
2.5%
2025-08-11T00:59:15.523037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
L 1397
31.9%
v 1311
29.9%
l 1311
29.9%
B 63
 
1.4%
n 63
 
1.4%
k 63
 
1.4%
H 50
 
1.1%
S 50
 
1.1%
o 36
 
0.8%
w 36
 
0.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4380
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
L 1397
31.9%
v 1311
29.9%
l 1311
29.9%
B 63
 
1.4%
n 63
 
1.4%
k 63
 
1.4%
H 50
 
1.1%
S 50
 
1.1%
o 36
 
0.8%
w 36
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4380
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
L 1397
31.9%
v 1311
29.9%
l 1311
29.9%
B 63
 
1.4%
n 63
 
1.4%
k 63
 
1.4%
H 50
 
1.1%
S 50
 
1.1%
o 36
 
0.8%
w 36
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4380
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
L 1397
31.9%
v 1311
29.9%
l 1311
29.9%
B 63
 
1.4%
n 63
 
1.4%
k 63
 
1.4%
H 50
 
1.1%
S 50
 
1.1%
o 36
 
0.8%
w 36
 
0.8%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:15.603740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4380
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGtl
2nd rowGtl
3rd rowGtl
4th rowGtl
5th rowGtl
ValueCountFrequency (%)
gtl 1382
94.7%
mod 65
 
4.5%
sev 13
 
0.9%
2025-08-11T00:59:15.796273image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 1382
31.6%
t 1382
31.6%
l 1382
31.6%
M 65
 
1.5%
o 65
 
1.5%
d 65
 
1.5%
S 13
 
0.3%
e 13
 
0.3%
v 13
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4380
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 1382
31.6%
t 1382
31.6%
l 1382
31.6%
M 65
 
1.5%
o 65
 
1.5%
d 65
 
1.5%
S 13
 
0.3%
e 13
 
0.3%
v 13
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4380
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 1382
31.6%
t 1382
31.6%
l 1382
31.6%
M 65
 
1.5%
o 65
 
1.5%
d 65
 
1.5%
S 13
 
0.3%
e 13
 
0.3%
v 13
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4380
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 1382
31.6%
t 1382
31.6%
l 1382
31.6%
M 65
 
1.5%
o 65
 
1.5%
d 65
 
1.5%
S 13
 
0.3%
e 13
 
0.3%
v 13
 
0.3%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:15.914215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.299315068
Min length4

Characters and Unicode

Total characters6277
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1Fam
2nd row1Fam
3rd row1Fam
4th row1Fam
5th row1Fam
ValueCountFrequency (%)
1fam 1220
83.6%
twnhse 114
 
7.8%
duplex 52
 
3.6%
twnhs 43
 
2.9%
2fmcon 31
 
2.1%
2025-08-11T00:59:16.160696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 1251
19.9%
1 1220
19.4%
F 1220
19.4%
a 1220
19.4%
n 188
 
3.0%
T 157
 
2.5%
w 157
 
2.5%
h 157
 
2.5%
s 157
 
2.5%
E 114
 
1.8%
Other values (10) 436
 
6.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6277
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
m 1251
19.9%
1 1220
19.4%
F 1220
19.4%
a 1220
19.4%
n 188
 
3.0%
T 157
 
2.5%
w 157
 
2.5%
h 157
 
2.5%
s 157
 
2.5%
E 114
 
1.8%
Other values (10) 436
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6277
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
m 1251
19.9%
1 1220
19.4%
F 1220
19.4%
a 1220
19.4%
n 188
 
3.0%
T 157
 
2.5%
w 157
 
2.5%
h 157
 
2.5%
s 157
 
2.5%
E 114
 
1.8%
Other values (10) 436
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6277
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
m 1251
19.9%
1 1220
19.4%
F 1220
19.4%
a 1220
19.4%
n 188
 
3.0%
T 157
 
2.5%
w 157
 
2.5%
h 157
 
2.5%
s 157
 
2.5%
E 114
 
1.8%
Other values (10) 436
 
6.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:16.218626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1460
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowY
4th rowY
5th rowY
ValueCountFrequency (%)
y 1365
93.5%
n 95
 
6.5%
2025-08-11T00:59:16.386866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1365
93.5%
N 95
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1460
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Y 1365
93.5%
N 95
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1460
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Y 1365
93.5%
N 95
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1460
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Y 1365
93.5%
N 95
 
6.5%
Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:16.552891image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.996575342
Min length4

Characters and Unicode

Total characters10215
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.3%

Sample

1st rowCompShg
2nd rowCompShg
3rd rowCompShg
4th rowCompShg
5th rowCompShg
ValueCountFrequency (%)
compshg 1434
98.2%
tar&grv 11
 
0.8%
wdshngl 6
 
0.4%
wdshake 5
 
0.3%
metal 1
 
0.1%
membran 1
 
0.1%
roll 1
 
0.1%
clytile 1
 
0.1%
2025-08-11T00:59:16.837316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 1445
14.1%
h 1445
14.1%
g 1440
14.1%
C 1435
14.0%
o 1435
14.0%
m 1435
14.0%
p 1434
14.0%
r 23
 
0.2%
a 18
 
0.2%
T 12
 
0.1%
Other values (15) 93
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10215
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 1445
14.1%
h 1445
14.1%
g 1440
14.1%
C 1435
14.0%
o 1435
14.0%
m 1435
14.0%
p 1434
14.0%
r 23
 
0.2%
a 18
 
0.2%
T 12
 
0.1%
Other values (15) 93
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10215
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 1445
14.1%
h 1445
14.1%
g 1440
14.1%
C 1435
14.0%
o 1435
14.0%
m 1435
14.0%
p 1434
14.0%
r 23
 
0.2%
a 18
 
0.2%
T 12
 
0.1%
Other values (15) 93
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10215
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 1445
14.1%
h 1445
14.1%
g 1440
14.1%
C 1435
14.0%
o 1435
14.0%
m 1435
14.0%
p 1434
14.0%
r 23
 
0.2%
a 18
 
0.2%
T 12
 
0.1%
Other values (15) 93
 
0.9%

BsmtFinType1
Text

Missing 

Distinct6
Distinct (%)0.4%
Missing37
Missing (%)2.5%
Memory size11.5 KiB
2025-08-11T00:59:16.997897image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4269
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGLQ
2nd rowALQ
3rd rowGLQ
4th rowALQ
5th rowGLQ
ValueCountFrequency (%)
unf 430
30.2%
glq 418
29.4%
alq 220
15.5%
blq 148
 
10.4%
rec 133
 
9.3%
lwq 74
 
5.2%
2025-08-11T00:59:17.295633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Q 860
20.1%
L 860
20.1%
U 430
10.1%
n 430
10.1%
f 430
10.1%
G 418
9.8%
A 220
 
5.2%
B 148
 
3.5%
R 133
 
3.1%
e 133
 
3.1%
Other values (2) 207
 
4.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4269
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Q 860
20.1%
L 860
20.1%
U 430
10.1%
n 430
10.1%
f 430
10.1%
G 418
9.8%
A 220
 
5.2%
B 148
 
3.5%
R 133
 
3.1%
e 133
 
3.1%
Other values (2) 207
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4269
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Q 860
20.1%
L 860
20.1%
U 430
10.1%
n 430
10.1%
f 430
10.1%
G 418
9.8%
A 220
 
5.2%
B 148
 
3.5%
R 133
 
3.1%
e 133
 
3.1%
Other values (2) 207
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4269
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Q 860
20.1%
L 860
20.1%
U 430
10.1%
n 430
10.1%
f 430
10.1%
G 418
9.8%
A 220
 
5.2%
B 148
 
3.5%
R 133
 
3.1%
e 133
 
3.1%
Other values (2) 207
 
4.8%

BsmtQual
Text

Missing 

Distinct4
Distinct (%)0.3%
Missing37
Missing (%)2.5%
Memory size11.5 KiB
2025-08-11T00:59:17.450976image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2846
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGd
2nd rowGd
3rd rowGd
4th rowTA
5th rowGd
ValueCountFrequency (%)
ta 649
45.6%
gd 618
43.4%
ex 121
 
8.5%
fa 35
 
2.5%
2025-08-11T00:59:17.706361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 649
22.8%
A 649
22.8%
G 618
21.7%
d 618
21.7%
E 121
 
4.3%
x 121
 
4.3%
F 35
 
1.2%
a 35
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2846
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 649
22.8%
A 649
22.8%
G 618
21.7%
d 618
21.7%
E 121
 
4.3%
x 121
 
4.3%
F 35
 
1.2%
a 35
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2846
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 649
22.8%
A 649
22.8%
G 618
21.7%
d 618
21.7%
E 121
 
4.3%
x 121
 
4.3%
F 35
 
1.2%
a 35
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2846
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 649
22.8%
A 649
22.8%
G 618
21.7%
d 618
21.7%
E 121
 
4.3%
x 121
 
4.3%
F 35
 
1.2%
a 35
 
1.2%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:17.765198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.034246575
Min length2

Characters and Unicode

Total characters2970
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRL
2nd rowRL
3rd rowRL
4th rowRL
5th rowRL
ValueCountFrequency (%)
rl 1151
78.3%
rm 218
 
14.8%
fv 65
 
4.4%
rh 16
 
1.1%
c 10
 
0.7%
all 10
 
0.7%
2025-08-11T00:59:17.943723image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 1385
46.6%
L 1151
38.8%
M 218
 
7.3%
F 65
 
2.2%
V 65
 
2.2%
l 20
 
0.7%
H 16
 
0.5%
C 10
 
0.3%
10
 
0.3%
( 10
 
0.3%
Other values (2) 20
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2970
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
R 1385
46.6%
L 1151
38.8%
M 218
 
7.3%
F 65
 
2.2%
V 65
 
2.2%
l 20
 
0.7%
H 16
 
0.5%
C 10
 
0.3%
10
 
0.3%
( 10
 
0.3%
Other values (2) 20
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2970
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
R 1385
46.6%
L 1151
38.8%
M 218
 
7.3%
F 65
 
2.2%
V 65
 
2.2%
l 20
 
0.7%
H 16
 
0.5%
C 10
 
0.3%
10
 
0.3%
( 10
 
0.3%
Other values (2) 20
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2970
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
R 1385
46.6%
L 1151
38.8%
M 218
 
7.3%
F 65
 
2.2%
V 65
 
2.2%
l 20
 
0.7%
H 16
 
0.5%
C 10
 
0.3%
10
 
0.3%
( 10
 
0.3%
Other values (2) 20
 
0.7%

Alley
Text

Missing 

Distinct2
Distinct (%)2.2%
Missing1369
Missing (%)93.8%
Memory size11.5 KiB
2025-08-11T00:59:18.068458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters364
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGrvl
2nd rowPave
3rd rowPave
4th rowGrvl
5th rowPave
ValueCountFrequency (%)
grvl 50
54.9%
pave 41
45.1%
2025-08-11T00:59:18.298137image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
v 91
25.0%
G 50
13.7%
r 50
13.7%
l 50
13.7%
P 41
11.3%
a 41
11.3%
e 41
11.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 364
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
v 91
25.0%
G 50
13.7%
r 50
13.7%
l 50
13.7%
P 41
11.3%
a 41
11.3%
e 41
11.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 364
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
v 91
25.0%
G 50
13.7%
r 50
13.7%
l 50
13.7%
P 41
11.3%
a 41
11.3%
e 41
11.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 364
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
v 91
25.0%
G 50
13.7%
r 50
13.7%
l 50
13.7%
P 41
11.3%
a 41
11.3%
e 41
11.3%
Distinct7
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:18.407480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.057534247
Min length3

Characters and Unicode

Total characters4464
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowTyp
2nd rowTyp
3rd rowTyp
4th rowTyp
5th rowTyp
ValueCountFrequency (%)
typ 1360
93.2%
min2 34
 
2.3%
min1 31
 
2.1%
mod 15
 
1.0%
maj1 14
 
1.0%
maj2 5
 
0.3%
sev 1
 
0.1%
2025-08-11T00:59:18.646353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 1360
30.5%
y 1360
30.5%
p 1360
30.5%
M 99
 
2.2%
i 65
 
1.5%
n 65
 
1.5%
1 45
 
1.0%
2 39
 
0.9%
a 19
 
0.4%
j 19
 
0.4%
Other values (5) 33
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4464
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 1360
30.5%
y 1360
30.5%
p 1360
30.5%
M 99
 
2.2%
i 65
 
1.5%
n 65
 
1.5%
1 45
 
1.0%
2 39
 
0.9%
a 19
 
0.4%
j 19
 
0.4%
Other values (5) 33
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4464
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 1360
30.5%
y 1360
30.5%
p 1360
30.5%
M 99
 
2.2%
i 65
 
1.5%
n 65
 
1.5%
1 45
 
1.0%
2 39
 
0.9%
a 19
 
0.4%
j 19
 
0.4%
Other values (5) 33
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4464
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 1360
30.5%
y 1360
30.5%
p 1360
30.5%
M 99
 
2.2%
i 65
 
1.5%
n 65
 
1.5%
1 45
 
1.0%
2 39
 
0.9%
a 19
 
0.4%
j 19
 
0.4%
Other values (5) 33
 
0.7%

GarageType
Text

Missing 

Distinct6
Distinct (%)0.4%
Missing81
Missing (%)5.5%
Memory size11.5 KiB
2025-08-11T00:59:18.805697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.084118927
Min length6

Characters and Unicode

Total characters8390
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAttchd
2nd rowAttchd
3rd rowAttchd
4th rowDetchd
5th rowAttchd
ValueCountFrequency (%)
attchd 870
63.1%
detchd 387
28.1%
builtin 88
 
6.4%
basment 19
 
1.4%
carport 9
 
0.7%
2types 6
 
0.4%
2025-08-11T00:59:19.065869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2243
26.7%
c 1257
15.0%
h 1257
15.0%
d 1257
15.0%
A 870
 
10.4%
e 412
 
4.9%
D 387
 
4.6%
B 107
 
1.3%
n 107
 
1.3%
u 88
 
1.0%
Other values (14) 405
 
4.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8390
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 2243
26.7%
c 1257
15.0%
h 1257
15.0%
d 1257
15.0%
A 870
 
10.4%
e 412
 
4.9%
D 387
 
4.6%
B 107
 
1.3%
n 107
 
1.3%
u 88
 
1.0%
Other values (14) 405
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8390
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 2243
26.7%
c 1257
15.0%
h 1257
15.0%
d 1257
15.0%
A 870
 
10.4%
e 412
 
4.9%
D 387
 
4.6%
B 107
 
1.3%
n 107
 
1.3%
u 88
 
1.0%
Other values (14) 405
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8390
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 2243
26.7%
c 1257
15.0%
h 1257
15.0%
d 1257
15.0%
A 870
 
10.4%
e 412
 
4.9%
D 387
 
4.6%
B 107
 
1.3%
n 107
 
1.3%
u 88
 
1.0%
Other values (14) 405
 
4.8%

GarageCond
Text

Missing 

Distinct5
Distinct (%)0.4%
Missing81
Missing (%)5.5%
Memory size11.5 KiB
2025-08-11T00:59:19.157830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2758
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTA
2nd rowTA
3rd rowTA
4th rowTA
5th rowTA
ValueCountFrequency (%)
ta 1326
96.2%
fa 35
 
2.5%
gd 9
 
0.7%
po 7
 
0.5%
ex 2
 
0.1%
2025-08-11T00:59:19.372769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 1326
48.1%
A 1326
48.1%
F 35
 
1.3%
a 35
 
1.3%
G 9
 
0.3%
d 9
 
0.3%
P 7
 
0.3%
o 7
 
0.3%
E 2
 
0.1%
x 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2758
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 1326
48.1%
A 1326
48.1%
F 35
 
1.3%
a 35
 
1.3%
G 9
 
0.3%
d 9
 
0.3%
P 7
 
0.3%
o 7
 
0.3%
E 2
 
0.1%
x 2
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2758
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 1326
48.1%
A 1326
48.1%
F 35
 
1.3%
a 35
 
1.3%
G 9
 
0.3%
d 9
 
0.3%
P 7
 
0.3%
o 7
 
0.3%
E 2
 
0.1%
x 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2758
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 1326
48.1%
A 1326
48.1%
F 35
 
1.3%
a 35
 
1.3%
G 9
 
0.3%
d 9
 
0.3%
P 7
 
0.3%
o 7
 
0.3%
E 2
 
0.1%
x 2
 
0.1%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:19.528676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.959589041
Min length3

Characters and Unicode

Total characters8701
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowInside
2nd rowFR2
3rd rowInside
4th rowCorner
5th rowFR2
ValueCountFrequency (%)
inside 1052
72.1%
corner 263
 
18.0%
culdsac 94
 
6.4%
fr2 47
 
3.2%
fr3 4
 
0.3%
2025-08-11T00:59:19.805114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1315
15.1%
e 1315
15.1%
I 1052
12.1%
s 1052
12.1%
i 1052
12.1%
d 1052
12.1%
r 526
 
6.0%
C 357
 
4.1%
o 263
 
3.0%
u 94
 
1.1%
Other values (9) 623
7.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8701
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1315
15.1%
e 1315
15.1%
I 1052
12.1%
s 1052
12.1%
i 1052
12.1%
d 1052
12.1%
r 526
 
6.0%
C 357
 
4.1%
o 263
 
3.0%
u 94
 
1.1%
Other values (9) 623
7.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8701
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1315
15.1%
e 1315
15.1%
I 1052
12.1%
s 1052
12.1%
i 1052
12.1%
d 1052
12.1%
r 526
 
6.0%
C 357
 
4.1%
o 263
 
3.0%
u 94
 
1.1%
Other values (9) 623
7.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8701
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1315
15.1%
e 1315
15.1%
I 1052
12.1%
s 1052
12.1%
i 1052
12.1%
d 1052
12.1%
r 526
 
6.0%
C 357
 
4.1%
o 263
 
3.0%
u 94
 
1.1%
Other values (9) 623
7.2%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:19.856615image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1460
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowY
4th rowY
5th rowY
ValueCountFrequency (%)
y 1340
91.8%
n 90
 
6.2%
p 30
 
2.1%
2025-08-11T00:59:20.023543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1340
91.8%
N 90
 
6.2%
P 30
 
2.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1460
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Y 1340
91.8%
N 90
 
6.2%
P 30
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1460
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Y 1340
91.8%
N 90
 
6.2%
P 30
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1460
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Y 1340
91.8%
N 90
 
6.2%
P 30
 
2.1%

MasVnrType
Text

Missing 

Distinct3
Distinct (%)0.5%
Missing872
Missing (%)59.7%
Memory size11.5 KiB
2025-08-11T00:59:20.172237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.539115646
Min length5

Characters and Unicode

Total characters3845
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBrkFace
2nd rowBrkFace
3rd rowBrkFace
4th rowStone
5th rowStone
ValueCountFrequency (%)
brkface 445
75.7%
stone 128
 
21.8%
brkcmn 15
 
2.6%
2025-08-11T00:59:20.430107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 573
14.9%
r 460
12.0%
k 460
12.0%
B 460
12.0%
F 445
11.6%
a 445
11.6%
c 445
11.6%
n 143
 
3.7%
S 128
 
3.3%
t 128
 
3.3%
Other values (3) 158
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3845
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 573
14.9%
r 460
12.0%
k 460
12.0%
B 460
12.0%
F 445
11.6%
a 445
11.6%
c 445
11.6%
n 143
 
3.7%
S 128
 
3.3%
t 128
 
3.3%
Other values (3) 158
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3845
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 573
14.9%
r 460
12.0%
k 460
12.0%
B 460
12.0%
F 445
11.6%
a 445
11.6%
c 445
11.6%
n 143
 
3.7%
S 128
 
3.3%
t 128
 
3.3%
Other values (3) 158
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3845
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 573
14.9%
r 460
12.0%
k 460
12.0%
B 460
12.0%
F 445
11.6%
a 445
11.6%
c 445
11.6%
n 143
 
3.7%
S 128
 
3.3%
t 128
 
3.3%
Other values (3) 158
 
4.1%
Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:20.547181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.000684932
Min length4

Characters and Unicode

Total characters5841
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowGasA
2nd rowGasA
3rd rowGasA
4th rowGasA
5th rowGasA
ValueCountFrequency (%)
gasa 1428
97.8%
gasw 18
 
1.2%
grav 7
 
0.5%
wall 4
 
0.3%
othw 2
 
0.1%
floor 1
 
0.1%
2025-08-11T00:59:20.779715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1457
24.9%
G 1453
24.9%
s 1446
24.8%
A 1428
24.4%
W 24
 
0.4%
l 9
 
0.2%
r 8
 
0.1%
v 7
 
0.1%
O 2
 
< 0.1%
t 2
 
< 0.1%
Other values (3) 5
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5841
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1457
24.9%
G 1453
24.9%
s 1446
24.8%
A 1428
24.4%
W 24
 
0.4%
l 9
 
0.2%
r 8
 
0.1%
v 7
 
0.1%
O 2
 
< 0.1%
t 2
 
< 0.1%
Other values (3) 5
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5841
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1457
24.9%
G 1453
24.9%
s 1446
24.8%
A 1428
24.4%
W 24
 
0.4%
l 9
 
0.2%
r 8
 
0.1%
v 7
 
0.1%
O 2
 
< 0.1%
t 2
 
< 0.1%
Other values (3) 5
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5841
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1457
24.9%
G 1453
24.9%
s 1446
24.8%
A 1428
24.4%
W 24
 
0.4%
l 9
 
0.2%
r 8
 
0.1%
v 7
 
0.1%
O 2
 
< 0.1%
t 2
 
< 0.1%
Other values (3) 5
 
0.1%
Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:20.908691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.62260274
Min length3

Characters and Unicode

Total characters6749
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGable
2nd rowGable
3rd rowGable
4th rowGable
5th rowGable
ValueCountFrequency (%)
gable 1141
78.2%
hip 286
 
19.6%
flat 13
 
0.9%
gambrel 11
 
0.8%
mansard 7
 
0.5%
shed 2
 
0.1%
2025-08-11T00:59:21.164208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1179
17.5%
l 1165
17.3%
e 1154
17.1%
G 1152
17.1%
b 1152
17.1%
H 286
 
4.2%
i 286
 
4.2%
p 286
 
4.2%
r 18
 
0.3%
F 13
 
0.2%
Other values (8) 58
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6749
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1179
17.5%
l 1165
17.3%
e 1154
17.1%
G 1152
17.1%
b 1152
17.1%
H 286
 
4.2%
i 286
 
4.2%
p 286
 
4.2%
r 18
 
0.3%
F 13
 
0.2%
Other values (8) 58
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6749
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1179
17.5%
l 1165
17.3%
e 1154
17.1%
G 1152
17.1%
b 1152
17.1%
H 286
 
4.2%
i 286
 
4.2%
p 286
 
4.2%
r 18
 
0.3%
F 13
 
0.2%
Other values (8) 58
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6749
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1179
17.5%
l 1165
17.3%
e 1154
17.1%
G 1152
17.1%
b 1152
17.1%
H 286
 
4.2%
i 286
 
4.2%
p 286
 
4.2%
r 18
 
0.3%
F 13
 
0.2%
Other values (8) 58
 
0.9%
Distinct15
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:21.341801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.979452055
Min length5

Characters and Unicode

Total characters10190
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st rowVinylSd
2nd rowMetalSd
3rd rowVinylSd
4th rowWd Sdng
5th rowVinylSd
ValueCountFrequency (%)
vinylsd 515
30.9%
hdboard 222
13.3%
metalsd 220
13.2%
wd 206
 
12.4%
sdng 206
 
12.4%
plywood 108
 
6.5%
cemntbd 61
 
3.7%
brkface 50
 
3.0%
wdshing 26
 
1.6%
stucco 25
 
1.5%
Other values (6) 27
 
1.6%
2025-08-11T00:59:21.667600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1786
17.5%
S 1016
 
10.0%
l 844
 
8.3%
n 831
 
8.2%
y 623
 
6.1%
i 541
 
5.3%
V 515
 
5.1%
a 492
 
4.8%
o 468
 
4.6%
B 336
 
3.3%
Other values (22) 2738
26.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10190
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
d 1786
17.5%
S 1016
 
10.0%
l 844
 
8.3%
n 831
 
8.2%
y 623
 
6.1%
i 541
 
5.3%
V 515
 
5.1%
a 492
 
4.8%
o 468
 
4.6%
B 336
 
3.3%
Other values (22) 2738
26.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10190
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
d 1786
17.5%
S 1016
 
10.0%
l 844
 
8.3%
n 831
 
8.2%
y 623
 
6.1%
i 541
 
5.3%
V 515
 
5.1%
a 492
 
4.8%
o 468
 
4.6%
B 336
 
3.3%
Other values (22) 2738
26.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10190
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
d 1786
17.5%
S 1016
 
10.0%
l 844
 
8.3%
n 831
 
8.2%
y 623
 
6.1%
i 541
 
5.3%
V 515
 
5.1%
a 492
 
4.8%
o 468
 
4.6%
B 336
 
3.3%
Other values (22) 2738
26.9%
Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:21.837166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.515753425
Min length4

Characters and Unicode

Total characters8053
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPConc
2nd rowCBlock
3rd rowPConc
4th rowBrkTil
5th rowPConc
ValueCountFrequency (%)
pconc 647
44.3%
cblock 634
43.4%
brktil 146
 
10.0%
slab 24
 
1.6%
stone 6
 
0.4%
wood 3
 
0.2%
2025-08-11T00:59:22.100928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1293
16.1%
C 1281
15.9%
c 1281
15.9%
l 804
10.0%
k 780
9.7%
B 780
9.7%
n 653
8.1%
P 647
8.0%
r 146
 
1.8%
T 146
 
1.8%
Other values (8) 242
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8053
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 1293
16.1%
C 1281
15.9%
c 1281
15.9%
l 804
10.0%
k 780
9.7%
B 780
9.7%
n 653
8.1%
P 647
8.0%
r 146
 
1.8%
T 146
 
1.8%
Other values (8) 242
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8053
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 1293
16.1%
C 1281
15.9%
c 1281
15.9%
l 804
10.0%
k 780
9.7%
B 780
9.7%
n 653
8.1%
P 647
8.0%
r 146
 
1.8%
T 146
 
1.8%
Other values (8) 242
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8053
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 1293
16.1%
C 1281
15.9%
c 1281
15.9%
l 804
10.0%
k 780
9.7%
B 780
9.7%
n 653
8.1%
P 647
8.0%
r 146
 
1.8%
T 146
 
1.8%
Other values (8) 242
 
3.0%

BsmtCond
Text

Missing 

Distinct4
Distinct (%)0.3%
Missing37
Missing (%)2.5%
Memory size11.5 KiB
2025-08-11T00:59:22.193255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2846
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTA
2nd rowTA
3rd rowTA
4th rowGd
5th rowTA
ValueCountFrequency (%)
ta 1311
92.1%
gd 65
 
4.6%
fa 45
 
3.2%
po 2
 
0.1%
2025-08-11T00:59:22.386091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 1311
46.1%
A 1311
46.1%
G 65
 
2.3%
d 65
 
2.3%
F 45
 
1.6%
a 45
 
1.6%
P 2
 
0.1%
o 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2846
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 1311
46.1%
A 1311
46.1%
G 65
 
2.3%
d 65
 
2.3%
F 45
 
1.6%
a 45
 
1.6%
P 2
 
0.1%
o 2
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2846
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 1311
46.1%
A 1311
46.1%
G 65
 
2.3%
d 65
 
2.3%
F 45
 
1.6%
a 45
 
1.6%
P 2
 
0.1%
o 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2846
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 1311
46.1%
A 1311
46.1%
G 65
 
2.3%
d 65
 
2.3%
F 45
 
1.6%
a 45
 
1.6%
P 2
 
0.1%
o 2
 
0.1%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:22.476328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2920
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowEx
2nd rowEx
3rd rowEx
4th rowGd
5th rowEx
ValueCountFrequency (%)
ex 741
50.8%
ta 428
29.3%
gd 241
 
16.5%
fa 49
 
3.4%
po 1
 
0.1%
2025-08-11T00:59:22.679452image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 741
25.4%
x 741
25.4%
T 428
14.7%
A 428
14.7%
G 241
 
8.3%
d 241
 
8.3%
F 49
 
1.7%
a 49
 
1.7%
P 1
 
< 0.1%
o 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 741
25.4%
x 741
25.4%
T 428
14.7%
A 428
14.7%
G 241
 
8.3%
d 241
 
8.3%
F 49
 
1.7%
a 49
 
1.7%
P 1
 
< 0.1%
o 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 741
25.4%
x 741
25.4%
T 428
14.7%
A 428
14.7%
G 241
 
8.3%
d 241
 
8.3%
F 49
 
1.7%
a 49
 
1.7%
P 1
 
< 0.1%
o 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 741
25.4%
x 741
25.4%
T 428
14.7%
A 428
14.7%
G 241
 
8.3%
d 241
 
8.3%
F 49
 
1.7%
a 49
 
1.7%
P 1
 
< 0.1%
o 1
 
< 0.1%

GarageFinish
Text

Missing 

Distinct3
Distinct (%)0.2%
Missing81
Missing (%)5.5%
Memory size11.5 KiB
2025-08-11T00:59:22.807758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4137
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRFn
2nd rowRFn
3rd rowRFn
4th rowUnf
5th rowRFn
ValueCountFrequency (%)
unf 605
43.9%
rfn 422
30.6%
fin 352
25.5%
2025-08-11T00:59:23.043967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1379
33.3%
F 774
18.7%
U 605
14.6%
f 605
14.6%
R 422
 
10.2%
i 352
 
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4137
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1379
33.3%
F 774
18.7%
U 605
14.6%
f 605
14.6%
R 422
 
10.2%
i 352
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4137
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1379
33.3%
F 774
18.7%
U 605
14.6%
f 605
14.6%
R 422
 
10.2%
i 352
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4137
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1379
33.3%
F 774
18.7%
U 605
14.6%
f 605
14.6%
R 422
 
10.2%
i 352
 
8.5%
Distinct9
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:23.167417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.121232877
Min length4

Characters and Unicode

Total characters6017
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNorm
2nd rowFeedr
3rd rowNorm
4th rowNorm
5th rowNorm
ValueCountFrequency (%)
norm 1260
86.3%
feedr 81
 
5.5%
artery 48
 
3.3%
rran 26
 
1.8%
posn 19
 
1.3%
rrae 11
 
0.8%
posa 8
 
0.5%
rrnn 5
 
0.3%
rrne 2
 
0.1%
2025-08-11T00:59:23.417522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 1437
23.9%
o 1287
21.4%
N 1286
21.4%
m 1260
20.9%
e 223
 
3.7%
A 93
 
1.5%
R 88
 
1.5%
F 81
 
1.3%
d 81
 
1.3%
t 48
 
0.8%
Other values (4) 133
 
2.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6017
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 1437
23.9%
o 1287
21.4%
N 1286
21.4%
m 1260
20.9%
e 223
 
3.7%
A 93
 
1.5%
R 88
 
1.5%
F 81
 
1.3%
d 81
 
1.3%
t 48
 
0.8%
Other values (4) 133
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6017
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 1437
23.9%
o 1287
21.4%
N 1286
21.4%
m 1260
20.9%
e 223
 
3.7%
A 93
 
1.5%
R 88
 
1.5%
F 81
 
1.3%
d 81
 
1.3%
t 48
 
0.8%
Other values (4) 133
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6017
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 1437
23.9%
o 1287
21.4%
N 1286
21.4%
m 1260
20.9%
e 223
 
3.7%
A 93
 
1.5%
R 88
 
1.5%
F 81
 
1.3%
d 81
 
1.3%
t 48
 
0.8%
Other values (4) 133
 
2.2%
Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:23.540607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2920
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGd
2nd rowTA
3rd rowGd
4th rowTA
5th rowGd
ValueCountFrequency (%)
ta 906
62.1%
gd 488
33.4%
ex 52
 
3.6%
fa 14
 
1.0%
2025-08-11T00:59:23.771303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 906
31.0%
A 906
31.0%
G 488
16.7%
d 488
16.7%
E 52
 
1.8%
x 52
 
1.8%
F 14
 
0.5%
a 14
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 906
31.0%
A 906
31.0%
G 488
16.7%
d 488
16.7%
E 52
 
1.8%
x 52
 
1.8%
F 14
 
0.5%
a 14
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 906
31.0%
A 906
31.0%
G 488
16.7%
d 488
16.7%
E 52
 
1.8%
x 52
 
1.8%
F 14
 
0.5%
a 14
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2920
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 906
31.0%
A 906
31.0%
G 488
16.7%
d 488
16.7%
E 52
 
1.8%
x 52
 
1.8%
F 14
 
0.5%
a 14
 
0.5%

MiscFeature
Text

Missing 

Distinct4
Distinct (%)7.4%
Missing1406
Missing (%)96.3%
Memory size11.5 KiB
2025-08-11T00:59:23.885880image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters216
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowShed
2nd rowShed
3rd rowShed
4th rowShed
5th rowShed
ValueCountFrequency (%)
shed 49
90.7%
gar2 2
 
3.7%
othr 2
 
3.7%
tenc 1
 
1.9%
2025-08-11T00:59:24.131205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
h 51
23.6%
e 50
23.1%
S 49
22.7%
d 49
22.7%
r 4
 
1.9%
G 2
 
0.9%
a 2
 
0.9%
2 2
 
0.9%
O 2
 
0.9%
t 2
 
0.9%
Other values (3) 3
 
1.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 216
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
h 51
23.6%
e 50
23.1%
S 49
22.7%
d 49
22.7%
r 4
 
1.9%
G 2
 
0.9%
a 2
 
0.9%
2 2
 
0.9%
O 2
 
0.9%
t 2
 
0.9%
Other values (3) 3
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 216
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
h 51
23.6%
e 50
23.1%
S 49
22.7%
d 49
22.7%
r 4
 
1.9%
G 2
 
0.9%
a 2
 
0.9%
2 2
 
0.9%
O 2
 
0.9%
t 2
 
0.9%
Other values (3) 3
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 216
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
h 51
23.6%
e 50
23.1%
S 49
22.7%
d 49
22.7%
r 4
 
1.9%
G 2
 
0.9%
a 2
 
0.9%
2 2
 
0.9%
O 2
 
0.9%
t 2
 
0.9%
Other values (3) 3
 
1.4%
Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:24.281209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.910958904
Min length4

Characters and Unicode

Total characters8630
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2Story
2nd row1Story
3rd row2Story
4th row2Story
5th row2Story
ValueCountFrequency (%)
1story 726
49.7%
2story 445
30.5%
1.5fin 154
 
10.5%
slvl 65
 
4.5%
sfoyer 37
 
2.5%
1.5unf 14
 
1.0%
2.5unf 11
 
0.8%
2.5fin 8
 
0.5%
2025-08-11T00:59:24.553868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 1273
14.8%
o 1208
14.0%
y 1208
14.0%
r 1208
14.0%
t 1171
13.6%
1 894
10.4%
2 464
 
5.4%
F 199
 
2.3%
. 187
 
2.2%
5 187
 
2.2%
Other values (8) 631
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8630
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 1273
14.8%
o 1208
14.0%
y 1208
14.0%
r 1208
14.0%
t 1171
13.6%
1 894
10.4%
2 464
 
5.4%
F 199
 
2.3%
. 187
 
2.2%
5 187
 
2.2%
Other values (8) 631
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8630
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 1273
14.8%
o 1208
14.0%
y 1208
14.0%
r 1208
14.0%
t 1171
13.6%
1 894
10.4%
2 464
 
5.4%
F 199
 
2.3%
. 187
 
2.2%
5 187
 
2.2%
Other values (8) 631
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8630
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 1273
14.8%
o 1208
14.0%
y 1208
14.0%
r 1208
14.0%
t 1171
13.6%
1 894
10.4%
2 464
 
5.4%
F 199
 
2.3%
. 187
 
2.2%
5 187
 
2.2%
Other values (8) 631
7.3%

BsmtFinType2
Text

Missing 

Distinct6
Distinct (%)0.4%
Missing38
Missing (%)2.6%
Memory size11.5 KiB
2025-08-11T00:59:24.651446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4266
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnf
2nd rowUnf
3rd rowUnf
4th rowUnf
5th rowUnf
ValueCountFrequency (%)
unf 1256
88.3%
rec 54
 
3.8%
lwq 46
 
3.2%
blq 33
 
2.3%
alq 19
 
1.3%
glq 14
 
1.0%
2025-08-11T00:59:24.845560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 1256
29.4%
n 1256
29.4%
f 1256
29.4%
L 112
 
2.6%
Q 112
 
2.6%
R 54
 
1.3%
c 54
 
1.3%
e 54
 
1.3%
w 46
 
1.1%
B 33
 
0.8%
Other values (2) 33
 
0.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4266
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 1256
29.4%
n 1256
29.4%
f 1256
29.4%
L 112
 
2.6%
Q 112
 
2.6%
R 54
 
1.3%
c 54
 
1.3%
e 54
 
1.3%
w 46
 
1.1%
B 33
 
0.8%
Other values (2) 33
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4266
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 1256
29.4%
n 1256
29.4%
f 1256
29.4%
L 112
 
2.6%
Q 112
 
2.6%
R 54
 
1.3%
c 54
 
1.3%
e 54
 
1.3%
w 46
 
1.1%
B 33
 
0.8%
Other values (2) 33
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4266
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 1256
29.4%
n 1256
29.4%
f 1256
29.4%
L 112
 
2.6%
Q 112
 
2.6%
R 54
 
1.3%
c 54
 
1.3%
e 54
 
1.3%
w 46
 
1.1%
B 33
 
0.8%
Other values (2) 33
 
0.8%
Distinct9
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
2025-08-11T00:59:24.931020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.158219178
Min length2

Characters and Unicode

Total characters3151
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWD
2nd rowWD
3rd rowWD
4th rowWD
5th rowWD
ValueCountFrequency (%)
wd 1267
86.8%
new 122
 
8.4%
cod 43
 
2.9%
conld 9
 
0.6%
conli 5
 
0.3%
conlw 5
 
0.3%
cwd 4
 
0.3%
oth 3
 
0.2%
con 2
 
0.1%
2025-08-11T00:59:25.130929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
D 1323
42.0%
W 1271
40.3%
w 127
 
4.0%
N 122
 
3.9%
e 122
 
3.9%
C 68
 
2.2%
O 46
 
1.5%
o 21
 
0.7%
n 21
 
0.7%
L 19
 
0.6%
Other values (3) 11
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3151
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
D 1323
42.0%
W 1271
40.3%
w 127
 
4.0%
N 122
 
3.9%
e 122
 
3.9%
C 68
 
2.2%
O 46
 
1.5%
o 21
 
0.7%
n 21
 
0.7%
L 19
 
0.6%
Other values (3) 11
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3151
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
D 1323
42.0%
W 1271
40.3%
w 127
 
4.0%
N 122
 
3.9%
e 122
 
3.9%
C 68
 
2.2%
O 46
 
1.5%
o 21
 
0.7%
n 21
 
0.7%
L 19
 
0.6%
Other values (3) 11
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3151
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
D 1323
42.0%
W 1271
40.3%
w 127
 
4.0%
N 122
 
3.9%
e 122
 
3.9%
C 68
 
2.2%
O 46
 
1.5%
o 21
 
0.7%
n 21
 
0.7%
L 19
 
0.6%
Other values (3) 11
 
0.3%

BsmtExposure
Text

Missing 

Distinct4
Distinct (%)0.3%
Missing38
Missing (%)2.6%
Memory size11.5 KiB
2025-08-11T00:59:25.193294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2844
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowGd
3rd rowMn
4th rowNo
5th rowAv
ValueCountFrequency (%)
no 953
67.0%
av 221
 
15.5%
gd 134
 
9.4%
mn 114
 
8.0%
2025-08-11T00:59:25.703901image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 953
33.5%
o 953
33.5%
A 221
 
7.8%
v 221
 
7.8%
G 134
 
4.7%
d 134
 
4.7%
M 114
 
4.0%
n 114
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2844
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 953
33.5%
o 953
33.5%
A 221
 
7.8%
v 221
 
7.8%
G 134
 
4.7%
d 134
 
4.7%
M 114
 
4.0%
n 114
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2844
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 953
33.5%
o 953
33.5%
A 221
 
7.8%
v 221
 
7.8%
G 134
 
4.7%
d 134
 
4.7%
M 114
 
4.0%
n 114
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2844
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 953
33.5%
o 953
33.5%
A 221
 
7.8%
v 221
 
7.8%
G 134
 
4.7%
d 134
 
4.7%
M 114
 
4.0%
n 114
 
4.0%